ComplexWorld PhDs description
Student name:Manuela Sauer
Supervisor:Prof. Thomas Hauf
Entity:University of Hannover
Title (inc.CWW link if available):Intelligent Modeling the Impact of Unpredictable Adverse Weather on ATM Performance
Abstract:The primary objective of our PhD Project is to foster the understanding of the interaction between the two complex systems of adverse weather and air traffic, and to provide a tool in supporting pilots, ATM and ATC to mitigate the impact of the former on the latter. We choose a model approach, where we combine an adverse weather model with a global air traffic model by the model DIVMET. From the many types of hazardous weather patterns, we focus first on thunderstorms. DIVMET will realistically simulate the circumnavigation of a partially chaotic moving and developing field of thunderstorms and will be coupled with a global air traffic model in real-time simulations. Three major applications are foreseen: (1) studies on strategic route finding under slightly unpredictable or unknown weather conditions, (2) development of forecast guidance for controllers and pilots under adverse weather conditions, (3) diagnostic studies on weather related delays, costs, CO2 emissions and risks together with optimization strategies. Research questions are: Is it possible to cast the CDM process of pilot and ATC in an algorithm? Can we provide realistic solutions? What are the worst case weather scenarios? Where is air traffic most vulnerable to adverse weather? How beneficial is the effect of increased adverse weather knowledge? How to account for the stochastic nature of the problem? What is the impact of adverse weather and to what percentage can it be reduced? How to account for the pilot’s limited field of view?
The key focus will be on (1) the weather uncertainty and the optimum pilot response, (2) the apparent weather uncertainty if the pilot has only a limited field of view. A typical business case is a flight in a moonless night through a field of storms, similar to the AF 447 flight in 2009. The uncertainty is an apparent one, as it can be instantaneously removed with a new data source. Nevertheless, incomplete or wrong understanding of the aircraft environment including weather is the major cause of accidents “Controlled flight into terrain”.
The PhD Project will contribute to the overall weather impact management by providing a tool on the tactical but also pre-tactical phase.
Student name:Soufiane Bouarfa
Supervisor:Prof. Richard Curran, Prof. Henk Blom
Entity:Technical University of Delft
Title (inc.CWW link if available):Using a Multi-Agent Systems Approach to Model and Analyze Resilience by Airline Operations Control
Abstract:The resilience of the current air transportation system is implicitly tested around the globe on a regular basis. Each day of operation, the system is perturbed by disturbances of different nature ranging from severe weather conditions, through airport congestion, up to an aircraft mechanical failure. In most of these cases, humans operating at the sharp edge assure efficient and safe air transportation amidst various uncertainties and disturbances. Motivated by the need to understand such a human-invoked resilience, this research explores a multi-agent systems approach to model part of the socio-technical air transportation system. The focus is on Airline Operations Control (AOC) where decision-making by the human operators facilitate disruption recovery.
Student name:Bernardo Monechi
Supervisor:Prof. Vittorio Loreto
Entity:Sapienza University of Rome
Title (inc.CWW link if available):Assessment of critical delay pattern and avalanche dynamics in the ATM system
Abstract:The importance of air transport has considerably grown in time, being nowadays an essential fast mean to connect national and international locations. Despite the competition with other new transportation systems, above all high-speed railways, and the recent economical crisis that reduced the load of traffic, an increase of air traffic demand over Europe has been forecast in the coming years. This growth of the traffic load could bring the actual Air Traffic Management system (ATM) over its capacity limits so that safety standards and performances might not be guaranteed anymore. Hence, it is important to understand the limits and the features of the current system, seeking for new solutions aimed at improving its capacity. In the current ATM system each aircraft is supposed to fly over predefined ``airways" between some geographical references called navigation points. Safety standards are guaranteed by air traffic controllers, whose duty is to prevent aircraft from getting too close each other. In order to guarantee such separation, controllers can perform easily the required redirections without the need of following the established preexistent airways. The aim of this PhD activity is to study and model the current Air Traffic Control system within the framework of complex systems and complex networks. At the current state we developed a simplified model of Air Traffic Control, where air traffic is regulated by controllers who provide the necessary safety separation between aircrafts while trying to minimize flight delays. As the traffic load increases, the model shows a phase transition from a phase in which all conflicts are resolved irrespective to the traffic pattern injected in the system, to a phase in which many conflicts cannot be resolved anymore. The model has been tested on idealized airspaces as well as on realistic arispaces build using real historical data about flights in the European Airspace. Besides the presence of a transition, the model is able to reproduce some finding coming from the data and thus it is likely capable to reproduce the real behaviour of the controllers although in a simplified way. This model could help to study and understand the criticality of the current system as well as to test for possible solutions in order aimed at improving the performance and capacity of the system in future scenarios.
Student name:Pablo Fleurquín
Supervisor:Dr. José J. Ramasco, Dr. Víctor M.Eguiluz
Entity: IFISC- University of Balearic Islands
Title (inc.CWW link if available):Analysis of air transportation using complex networks
Abstract:Delay propagation is the result of different factors, including the lack of coordination of airline flight schedules, finely tuned airline flight schedules with little slack time to dampen delay propagation, high levels of congestion preventing re-accommodation of delayed flights, or high aircraft load factors preventing timely re-accommodation of passengers who misconnect or whose flights are cancelled. All combine to create passenger disruptions and lengthy passenger waits that exceed the levels of flight delays. According to the 2008 Report of the Congress Joint Economic Committee, flight delays have an economic impact in the U.S. equivalent to 40.7 billions of dollars per year[1], while a similar cost is expected in Europe[2][3]. The situation can turn even grimmer in the next decade since the air traffic is envisaged to increase[4]. This includes higher emissions to recover delays, image loss for the companies and missed business oportunities and leisure time for passengers. Models and methods allowing stakeholders to characterize mechanisms behind delay propagation, to forecast network congestion, and to optimize planning and operational practices to mitigate delays are thus of great relevance. At the current state we defined a set of metrics able to quantify the level of network congestion and developed an agent-based data-driven model that reproduces the delay propagation patterns observed in the U.S. performance data. Our results indicate that there is a non-negligible risk of systemic instability even under normal operating conditions. We also identify passenger and crew connectivity as the most relevant internal factor contributing to delay spreading.
Student name:Andreas Heidt
Supervisor: Prof. Alexander Martin
Entity:Friedrich Alexander University
Title (inc.CWW link if available):Uncertainty Models for Optimal and Robust ATM Schedules
Abstract:One of the main tasks of ATM is planning, particularly scheduling limited resources such as runway capacity, aircraft, fuel, passenger routes, and arrival and departure routes. The air transport system is however constantly influenced by internal as well as external events that have to be taken into account. Since these uncertainties are inevitable, we have to accept these phenomena and have to incorporate uncertainty into the models, with the aim of getting robust plans with respect to the data. Without robustness we would achieve plans that suffer from uncertainty and have to be changed regularly. As such, the goal is to use resources more efficiently and provide better support for ATM controllers. The PhD project focusses on modeling ATM planning problems in a mathematically robust way. Therefore mathematical models have to be considered and made more robust. To solve these models new effective algorithms and solution techniques have to be developed to cope with uncertainty and non-determinism.
Student name:Nataliya Mogles
Supervisor: Prof. Jan Treur
Entity:Vrije University of Amsterdam
Title (inc.CWW link if available):Interlevel Relations between Models within Air Traffic Management (ATM)
Abstract:According to the SESAR programme, the future ATM system will consist of a large number of (both human and automated) agents at different levels of the ATM process, which collaborate in a sophisticated and resilient manner in order to achieve optimal performance with minimal chance of hazardous events. To study the emergent behaviour of this complex system, the current project proposes to exploit computational modeling techniques. More specifically, the proposal is to model the behaviour of the ATM system along three abstraction or aggregation dimensions (the temporal dimension, the process abstraction dimension, and the agent clustering dimension)[1]. For each dimension, computational models will be developed at different levels of aggregation. By establishing formal (mathematical and logical) relations between the models at the different levels, it will then be possible to relate emergent phenomena to (and explain them in terms of) local mechanisms. Thus, the developed computational models and interlevel relations will provide more insight in the types of skills and properties that are required for (both human and software) agents involved in ATM processes, to ensure the emergence of optimal performance in the overall system with minimal errors. Such insights may be used, among others, to increase awareness of weaknesses and bottlenecks in the organization, and to develop more effective training methods for human operators as well as more effective automated systems.
Student name:Dilhan J. Thilakarathne
Supervisor: Prof. Dr. Jan Treur, Prof. Dr. Tibor Bosse
Entity:Vrije University of Amsterdam
Title (inc.CWW link if available): Computational Cognitive Modeling of Situation Awareness in ATM
Abstract: Situation(al) Awareness is commonly agreed to be an important concept in the study of safety critical systems in which both humans and technical systems are involved, ex. Air Traffic Management (ATM). Although the concept has received considerable attention in the literature, many questions are still unanswered, most of which are related to the scientific underpinning of Situation Awareness from a Cognitive (Neuro)Science perspective. Studying Situation Awareness from a neuro-cognitive perspective in combination with computational modelling will be an interesting novel research direction. In the current project, dynamic computational models of Situation Awareness will be developed based on recent neurological literature, and will be applied to simulate real world ATM scenarios. By modeling the behavior of the human operators that play a role in these scenarios, the aim is to obtain more refined models and understanding of Situation Awareness in the context of ATM.